Self-Driving Cars Are Too Good at 3-Point Turns, So Google Dumbed Them Down

Teaching cars to drive themselves is only half the battle. The other half is teaching them to drive in a way that doesn't scare the hell out of their human occupants.

Consider the three-point turn, bane of student drivers everywhere. It's relatively simple to pull off on an open, straight road, as illustrated in the diagram above and video below. But roads are not always straight, and they're not always clear.

Google self-driving car working out a three-point turn. The purple boxes are parked cars.

Google

Google's self-driving cars must learn the maneuver for turning a car around in tight spaces if they're going to navigate our streets, and so they practice 1,000 multi-point turns every week on the streets of America. They're getting really good. So good, in fact, that Google had to change the way its cars execute the turn so as not to make passengers uncomfortable.

An autonomous car's sensors allow it to see in 360 degrees. It can determine its own position down to a few centimeters. Its computer can calculate the quickest way to pull off a three-point turn in any physical space, no matter how crowded it is with other cars and objects. If that means driving backward most of the time and passing damn close to another car, so be it. Machines don't care whether they're in reverse or drive, and don't get jittery when they're a few centimeters away from an insurance claim.

People do. We don't live driving backwards—it's unnatural and forces us to turn our necks to an awkward angle. We like to drive forward, where we can see everything. Google knows this. "So we've taught our cars to mimic these human patterns, favoring wider forward arcs, rather than a series of short movements back and forth," the company says in its October monthly report on its autonomous fleet.

The self-driving future is going to be weird. One way to reduce traffic jams is to have a fleet of autonomous vehicles that can talk to each other, allowing cars to stay closer to each other than would be possible with human drivers and our limited reaction times. That means trusting the machine, even if it feels totally, utterly unnatural.

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